{"total":185,"rows":[{"id":"2205.06743","title":"A Comprehensive Survey of Few-shot Learning: Evolution, Applications, Challenges, and Opportunities","created":"2022-05-13","cited_by_count":163,"area":null},{"id":"2104.03310","title":"Regularizing Generative Adversarial Networks under Limited Data","created":"2021-04-07","cited_by_count":107,"area":null},{"id":"2203.04291","title":"Learning from Few Examples: A Summary of Approaches to Few-Shot Learning","created":"2022-03-07","cited_by_count":86,"area":null},{"id":"2104.14385","title":"Cross-Domain Few-Shot Classification via Adversarial Task Augmentation","created":"2021-04-29","cited_by_count":63,"area":null},{"id":"2107.11355","title":"Unsupervised Domain Adaptive 3D Detection with Multi-Level Consistency","created":"2021-07-23","cited_by_count":63,"area":null},{"id":"2105.07029","title":"Learning a Universal Template for Few-shot Dataset Generalization","created":"2021-05-14","cited_by_count":61,"area":null},{"id":"2302.09309","title":"StyleAdv: Meta Style Adversarial Training for Cross-Domain Few-Shot Learning","created":"2023-02-18","cited_by_count":53,"area":null},{"id":"2108.05028","title":"Boosting the Generalization Capability in Cross-Domain Few-shot Learning via Noise-enhanced Supervised Autoencoder","created":"2021-08-11","cited_by_count":51,"area":null},{"id":"2103.15706","title":"StyleMeUp: Towards Style-Agnostic Sketch-Based Image Retrieval","created":"2021-03-29","cited_by_count":50,"area":null},{"id":"2204.04567","title":"Joint Distribution Matters: Deep Brownian Distance Covariance for Few-Shot Classification","created":"2022-04-09","cited_by_count":50,"area":null},{"id":"2101.02833","title":"Shallow Bayesian Meta Learning for Real-World Few-Shot Recognition","created":"2021-01-08","cited_by_count":48,"area":null},{"id":"2107.11978","title":"Meta-FDMixup: Cross-Domain Few-Shot Learning Guided by Labeled Target Data","created":"2021-07-26","cited_by_count":48,"area":null},{"id":"2402.03094","title":"Cross-Domain Few-Shot Object Detection via Enhanced Open-Set Object Detector","created":"2024-02-05","cited_by_count":43,"area":null},{"id":"2203.12175","title":"Adaptive Transformers for Robust Few-shot Cross-domain Face Anti-spoofing","created":"2022-03-23","cited_by_count":38,"area":null},{"id":"2202.01339","title":"Understanding Cross-Domain Few-Shot Learning Based on Domain Similarity and Few-Shot Difficulty","created":"2022-02-01","cited_by_count":37,"area":null},{"id":"2208.11021","title":"Adversarial Feature Augmentation for Cross-domain Few-shot Classification","created":"2022-08-23","cited_by_count":36,"area":null},{"id":"2401.08407","title":"Cross-Domain Few-Shot Segmentation via Iterative Support-Query Correspondence Mining","created":"2024-01-16","cited_by_count":30,"area":null},{"id":"2104.08481","title":"Revisiting Few-shot Relation Classification: Evaluation Data and Classification Schemes","created":"2021-04-17","cited_by_count":27,"area":null},{"id":"2112.00260","title":"Ranking Distance Calibration for Cross-Domain Few-Shot Learning","created":"2021-12-01","cited_by_count":27,"area":null},{"id":"2403.00567","title":"Flatten Long-Range Loss Landscapes for Cross-Domain Few-Shot Learning","created":"2024-03-01","cited_by_count":26,"area":null},{"id":"2204.00949","title":"Matching Feature Sets for Few-Shot Image Classification","created":"2022-04-02","cited_by_count":25,"area":null},{"id":"2210.07805","title":"Meta-Query-Net: Resolving Purity-Informativeness Dilemma in Open-set Active Learning","created":"2022-10-13","cited_by_count":25,"area":null},{"id":"2504.10685","title":"NTIRE 2025 Challenge on Cross-Domain Few-Shot Object Detection: Methods and Results","created":"2025-04-14","cited_by_count":25,"area":null},{"id":"2105.08149","title":"Deep Metric Learning for Few-Shot Image Classification: A Review of Recent Developments","created":"2021-05-17","cited_by_count":23,"area":null},{"id":"2203.07656","title":"Wave-SAN: Wavelet based Style Augmentation Network for Cross-Domain Few-Shot Learning","created":"2022-03-15","cited_by_count":23,"area":null},{"id":"2106.16245","title":"How to Train Your MAML to Excel in Few-Shot Classification","created":"2021-06-30","cited_by_count":22,"area":null},{"id":"2402.17614","title":"Adapt Before Comparison: A New Perspective on Cross-Domain Few-Shot Segmentation","created":"2024-02-27","cited_by_count":22,"area":null},{"id":"2206.00092","title":"FHIST: A Benchmark for Few-shot Classification of Histological Images","created":"2022-05-31","cited_by_count":20,"area":null},{"id":"2206.08126","title":"Channel Importance Matters in Few-Shot Image Classification","created":"2022-06-16","cited_by_count":20,"area":null},{"id":"2201.08265","title":"Cross-Domain Few-Shot Graph Classification","created":"2022-01-20","cited_by_count":19,"area":null},{"id":"2106.05517","title":"Learning to Affiliate: Mutual Centralized Learning for Few-shot Classification","created":"2021-06-10","cited_by_count":18,"area":null},{"id":"2207.11169","title":"Rethinking Few-Shot Object Detection on a Multi-Domain Benchmark","created":"2022-07-22","cited_by_count":17,"area":null},{"id":"2210.05311","title":"CD-FSOD: A Benchmark for Cross-domain Few-shot Object Detection","created":"2022-10-11","cited_by_count":17,"area":null},{"id":"2305.09269","title":"ContrastNet: A Contrastive Learning Framework for Few-Shot Text Classification","created":"2023-05-16","cited_by_count":17,"area":null},{"id":"2506.16330","title":"Reliable Few-shot Learning under Dual Noises","created":"2025-06-19","cited_by_count":17,"area":null},{"id":"2104.02638","title":"Comparing Transfer and Meta Learning Approaches on a Unified Few-Shot Classification Benchmark","created":"2021-04-06","cited_by_count":16,"area":null},{"id":"2107.00197","title":"Few-Shot Learning with a Strong Teacher","created":"2021-07-01","cited_by_count":16,"area":null},{"id":"2210.05392","title":"TGDM: Target Guided Dynamic Mixup for Cross-Domain Few-Shot Learning","created":"2022-10-11","cited_by_count":16,"area":null},{"id":"2301.02419","title":"Exploring Efficient Few-shot Adaptation for Vision Transformers","created":"2023-01-06","cited_by_count":16,"area":null},{"id":"2303.00996","title":"Unsupervised Meta-Learning via Few-shot Pseudo-supervised Contrastive Learning","created":"2023-03-02","cited_by_count":15,"area":null},{"id":"2306.10511","title":"Dual Adaptive Representation Alignment for Cross-domain Few-shot Learning","created":"2023-06-18","cited_by_count":15,"area":null},{"id":"2311.18649","title":"Simple Semantic-Aided Few-Shot Learning","created":"2023-11-30","cited_by_count":15,"area":null},{"id":"2506.05872","title":"Domain-RAG: Retrieval-Guided Compositional Image Generation for Cross-Domain Few-Shot Object Detection","created":"2025-06-06","cited_by_count":15,"area":null},{"id":"2109.09883","title":"On the Importance of Distractors for Few-Shot Classification","created":"2021-09-20","cited_by_count":14,"area":null},{"id":"2112.08181","title":"Hierarchical Variational Memory for Few-shot Learning Across Domains","created":"2021-12-15","cited_by_count":14,"area":null},{"id":"2208.10156","title":"Meta-Causal Feature Learning for Out-of-Distribution Generalization","created":"2022-08-22","cited_by_count":14,"area":null},{"id":"2209.01501","title":"Meta-Learning with Less Forgetting on Large-Scale Non-Stationary Task Distributions","created":"2022-09-03","cited_by_count":14,"area":null},{"id":"2303.08557","title":"Deep Learning for Cross-Domain Few-Shot Visual Recognition: A Survey","created":"2023-03-15","cited_by_count":14,"area":null},{"id":"2303.09128","title":"Exploring Distributional Shifts in Large Language Models for Code Analysis","created":"2023-03-16","cited_by_count":14,"area":null},{"id":"2405.19917","title":"Multimodal Cross-Domain Few-Shot Learning for Egocentric Action Recognition","created":"2024-05-30","cited_by_count":14,"area":"distill"},{"id":"2105.02692","title":"Learning to Perturb Word Embeddings for Out-of-distribution QA","created":"2021-05-06","cited_by_count":13,"area":null},{"id":"2403.01966","title":"Enhancing Information Maximization with Distance-Aware Contrastive Learning for Source-Free Cross-Domain Few-Shot Learning","created":"2024-03-04","cited_by_count":13,"area":null},{"id":"2604.11998","title":"The Second Challenge on Cross-Domain Few-Shot Object Detection at NTIRE 2026: Methods and Results","created":"2026-04-13","cited_by_count":13,"area":null},{"id":"2109.12548","title":"Disentangled Feature Representation for Few-shot Image Classification","created":"2021-09-26","cited_by_count":12,"area":null},{"id":"2303.09914","title":"Rehearsal-Free Domain Continual Face Anti-Spoofing: Generalize More and Forget Less","created":"2023-03-16","cited_by_count":12,"area":null},{"id":"2405.02996","title":"RepAugment: Input-Agnostic Representation-Level Augmentation for Respiratory Sound Classification","created":"2024-05-05","cited_by_count":12,"area":null},{"id":"2107.09242","title":"Boosting Few-Shot Classification with View-Learnable Contrastive Learning","created":"2021-07-20","cited_by_count":11,"area":null},{"id":"2411.01432","title":"Meta-Exploiting Frequency Prior for Cross-Domain Few-Shot Learning","created":"2024-11-03","cited_by_count":11,"area":null},{"id":"2101.07899","title":"Cross-domain few-shot learning with unlabelled data","created":"2021-01-19","cited_by_count":10,"area":null},{"id":"2109.03478","title":"Cross-Site Severity Assessment of COVID-19 from CT Images via Domain Adaptation","created":"2021-09-08","cited_by_count":10,"area":null},{"id":"2310.03843","title":"From Channel Bias to Feature Redundancy: Uncovering the \"Less is More\" Principle in Few-Shot Learning","created":"2023-10-05","cited_by_count":10,"area":null},{"id":"2412.00767","title":"Prompt as Free Lunch: Enhancing Diversity in Source-Free Cross-domain Few-shot Learning through Semantic-Guided Prompting","created":"2024-12-01","cited_by_count":10,"area":null},{"id":"2106.10575","title":"EvoGrad: Efficient Gradient-Based Meta-Learning and Hyperparameter Optimization","created":"2021-06-19","cited_by_count":9,"area":null},{"id":"2208.10930","title":"FS-BAN: Born-Again Networks for Domain Generalization Few-Shot Classification","created":"2022-08-23","cited_by_count":9,"area":null},{"id":"2210.05185","title":"Meta-Learning with Self-Improving Momentum Target","created":"2022-10-11","cited_by_count":9,"area":null},{"id":"2210.05280","title":"ME-D2N: Multi-Expert Domain Decompositional Network for Cross-Domain Few-Shot Learning","created":"2022-10-11","cited_by_count":9,"area":null},{"id":"2308.02877","title":"Meta-learning in healthcare: A survey","created":"2023-08-05","cited_by_count":9,"area":null},{"id":"2406.16422","title":"Exploring Cross-Domain Few-Shot Classification via Frequency-Aware Prompting","created":"2024-06-24","cited_by_count":9,"area":null},{"id":"2504.13112","title":"Hadamard product in deep learning: Introduction, Advances and Challenges","created":"2025-04-17","cited_by_count":9,"area":null},{"id":"2103.16009","title":"Revisiting Local Descriptor for Improved Few-Shot Classification","created":"2021-03-30","cited_by_count":8,"area":null},{"id":"2109.14120","title":"Meta Learning on a Sequence of Imbalanced Domains with Difficulty Awareness","created":"2021-09-29","cited_by_count":8,"area":null},{"id":"2305.12692","title":"MetaAdapt: Domain Adaptive Few-Shot Misinformation Detection via Meta Learning","created":"2023-05-22","cited_by_count":8,"area":null},{"id":"2310.18713","title":"Episodic Multi-Task Learning with Heterogeneous Neural Processes","created":"2023-10-28","cited_by_count":8,"area":null},{"id":"2208.10559","title":"Transductive Decoupled Variational Inference for Few-Shot Classification","created":"2022-08-22","cited_by_count":7,"area":null},{"id":"2211.14745","title":"Cross-domain Few-shot Segmentation with Transductive Fine-tuning","created":"2022-11-27","cited_by_count":7,"area":null},{"id":"2307.14709","title":"Taxonomy Adaptive Cross-Domain Adaptation in Medical Imaging via Optimization Trajectory Distillation","created":"2023-07-27","cited_by_count":7,"area":null},{"id":"2401.13987","title":"Cross-Domain Few-Shot Learning via Adaptive Transformer Networks","created":"2024-01-25","cited_by_count":7,"area":null},{"id":"2509.25033","title":"VT-FSL: Bridging Vision and Text with LLMs for Few-Shot Learning","created":"2025-09-29","cited_by_count":7,"area":null},{"id":"2109.07785","title":"MHFC: Multi-Head Feature Collaboration for Few-Shot Learning","created":"2021-09-16","cited_by_count":6,"area":null},{"id":"2205.05282","title":"ReFine: Re-randomization before Fine-tuning for Cross-domain Few-shot Learning","created":"2022-05-11","cited_by_count":6,"area":null},{"id":"2205.07874","title":"How to Fine-tune Models with Few Samples: Update, Data Augmentation, and Test-time Augmentation","created":"2022-05-13","cited_by_count":6,"area":null},{"id":"2207.10833","title":"Few-shot Image Generation Using Discrete Content Representation","created":"2022-07-22","cited_by_count":6,"area":null},{"id":"2305.14986","title":"Non-adversarial Robustness of Deep Learning Methods for Computer Vision","created":"2023-05-24","cited_by_count":6,"area":null},{"id":"2409.02882","title":"Benchmarking Spurious Bias in Few-Shot Image Classifiers","created":"2024-09-04","cited_by_count":6,"area":null},{"id":"2106.08112","title":"Contextualizing Meta-Learning via Learning to Decompose","created":"2021-06-15","cited_by_count":5,"area":null},{"id":"2108.02953","title":"Few-shot Unsupervised Domain Adaptation with Image-to-class Sparse Similarity Encoding","created":"2021-08-06","cited_by_count":5,"area":null},{"id":"2110.07510","title":"Omni-Training: Bridging Pre-Training and Meta-Training for Few-Shot Learning","created":"2021-10-14","cited_by_count":5,"area":null},{"id":"2112.00690","title":"MDFM: Multi-Decision Fusing Model for Few-Shot Learning","created":"2021-12-01","cited_by_count":5,"area":null},{"id":"2201.06781","title":"When Facial Expression Recognition Meets Few-Shot Learning: A Joint and Alternate Learning Framework","created":"2022-01-18","cited_by_count":5,"area":null},{"id":"2203.07738","title":"GCT: Graph Co-Training for Semi-Supervised Few-Shot Learning","created":"2022-03-15","cited_by_count":5,"area":null},{"id":"2206.15010","title":"\"Diversity and Uncertainty in Moderation\" are the Key to Data Selection for Multilingual Few-shot Transfer","created":"2022-06-30","cited_by_count":5,"area":null},{"id":"2207.07826","title":"Cross-Domain Cross-Set Few-Shot Learning via Learning Compact and Aligned Representations","created":"2022-07-16","cited_by_count":5,"area":null},{"id":"2303.06679","title":"RotoGBML: Towards Out-of-Distribution Generalization for Gradient-Based Meta-Learning","created":"2023-03-12","cited_by_count":5,"area":null},{"id":"2404.19644","title":"MetaCoCo: A New Few-Shot Classification Benchmark with Spurious Correlation","created":"2024-04-30","cited_by_count":5,"area":null},{"id":"2408.09722","title":"Towards Few-Shot Learning in the Open World: A Review and Beyond","created":"2024-08-19","cited_by_count":5,"area":null},{"id":"2411.10070","title":"Step-wise Distribution Alignment Guided Style Prompt Tuning for Source-free Cross-domain Few-shot Learning","created":"2024-11-15","cited_by_count":5,"area":null},{"id":"2103.09027","title":"Repurposing Pretrained Models for Robust Out-of-domain Few-Shot Learning","created":"2021-03-16","cited_by_count":4,"area":null},{"id":"2106.13899","title":"Domain Conditional Predictors for Domain Adaptation","created":"2021-06-25","cited_by_count":4,"area":null},{"id":"2108.08995","title":"Discriminative Domain-Invariant Adversarial Network for Deep Domain Generalization","created":"2021-08-20","cited_by_count":4,"area":null},{"id":"2109.01302","title":"Self-Taught Cross-Domain Few-Shot Learning with Weakly Supervised Object Localization and Task-Decomposition","created":"2021-09-03","cited_by_count":4,"area":null}],"next_cursor":"100"}